Measuring Healthcare Accessibility Through Clustering Techniques and Multi-layer Network Analysis

Balakrishnan D.; Drekshagen S.; Sahu V.; Tariverdi M.; Nunez-del-Prado M. · Communications in Computer and Information Science (2026) · DOI: 10.1007/978-3-032-20322-9_8

Resumen

Accessibility to health services, both in-person and virtual, is vital for advancing Health and Well-being SDG. While e-healthcare can bridge some of these gaps, its success depends on reliable digital infrastructure and coverage. This paper provides an integrated approach that considers both dimensions, physical and digital. We evaluate Multi-Edge Graph model, Multi-Layer Graph model, Composite index, and unsupervised learning approaches to measure physical and digital accessibility apply for South Africa. Our findings show that clustering methods, reinforced by robust imputation, afford the best balance between objectivity, interpretability, and actionable insights under the current data environment offering a scalable framework for assessing hybrid healthcare systems and provide valuable insights for policy, planning, and resource allocation. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.

Instituciones: Universidad Peruana de Ciencias Aplicadas